docstr: :param in_channels: 基础网络输出的维度
  :param kwargs:
docstr_tok: [":","param","in_channels",":","\u57fa\u7840\u7f51\u7edc\u8f93\u51fa\u7684\u7ef4\u5ea6",":","param","kwargs",":"]
code: def __init__(self, in_channels, inner_channels=256, **kwargs):
      """
      :param in_channels: 基础网络输出的维度
      :param kwargs:
      """
      super().__init__()
      inplace = True
      self.conv_out = inner_channels
      inner_channels = inner_channels // 4
      # reduce layers
      self.reduce_conv_c2 = ConvBnRelu(
          in_channels[0], inner_channels, kernel_size=1, inplace=inplace
      )
      self.reduce_conv_c3 = ConvBnRelu(
          in_channels[1], inner_channels, kernel_size=1, inplace=inplace
      )
      self.reduce_conv_c4 = ConvBnRelu(
          in_channels[2], inner_channels, kernel_size=1, inplace=inplace
      )
      self.reduce_conv_c5 = ConvBnRelu(
          in_channels[3], inner_channels, kernel_size=1, inplace=inplace
      )
      # Smooth layers
      self.smooth_p4 = ConvBnRelu(
          inner_channels,
          inner_channels,
          kernel_size=3,
          padding=1,
          inplace=inplace,
      )
      self.smooth_p3 = ConvBnRelu(
          inner_channels,
          inner_channels,
          kernel_size=3,
          padding=1,
          inplace=inplace,
      )
      self.smooth_p2 = ConvBnRelu(
          inner_channels,
          inner_channels,
          kernel_size=3,
          padding=1,
          inplace=inplace,
      )
  
      self.conv = nn.Sequential(
          nn.Conv2D(
              self.conv_out,
              self.conv_out,
              kernel_size=3,
              padding=1,
              stride=1,
          ),
          nn.BatchNorm2D(self.conv_out),
          nn.ReLU(),
      )
      self.out_channels = self.conv_out
  
file_path: PaddleOCR/benchmark/PaddleOCR_DBNet/models/neck/FPN.py
imports: import paddle
  import paddle.nn.functional
  from paddle import nn
  from models.basic import ConvBnRelu
label_desc: Use image node_id 1 to create a new FPN object from inherited base classes: nn with example: obj = FPN(in_channels, inner_channels)